Time-varying volatility asymmetry: a conditioned HAR-RV(CJ) EGARCH-M model

I develop a novel model that accounts for volatility feedback and leverage effects, effectively incorporating signed continuous and jump components of the realized variance into the variance specification through a heterogeneous autoregressive forecasting model. I then condition the variance specification on the lagged realized variance and the risk aversion to analyze eventual state-dependent variations in the volatility asymmetry. I find that the volatility asymmetry is clearly more pronounced in periods of market stress. In addition, I reveal a further asymmetry in the asymmetric reaction patterns of the volatility to good and bad news: investors become more sensitive to bad news in market downturns.